QuantLib 0.3.11
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Reference manual
OptimizationMethod Class Reference
#include <ql/Optimization/method.hpp>
Inheritance diagram for OptimizationMethod:
Detailed Description
Abstract class for constrained optimization method.
Public Member Functions | |
| void | setInitialValue (const Array &initialValue) |
| Set initial value. | |
| void | setEndCriteria (const EndCriteria &endCriteria) |
| Set optimization end criteria. | |
| Integer & | iterationNumber () const |
| current iteration number | |
| EndCriteria & | endCriteria () const |
| optimization end criteria | |
| Integer & | functionEvaluation () const |
| number of evaluation of cost function | |
| Integer & | gradientEvaluation () const |
| number of evaluation of cost function gradient | |
| Real & | functionValue () const |
| value of cost function | |
| Real & | gradientNormValue () const |
| value of cost function gradient norm | |
| Array & | x () const |
| current value of the local minimum | |
| Array & | searchDirection () const |
| current value of the search direction | |
| virtual void | minimize (const Problem &P) const =0 |
| minimize the optimization problem P | |
Protected Attributes | |
| Array | initialValue_ |
| initial value of unknowns | |
| Integer | iterationNumber_ |
| current iteration step in the Optimization process | |
| EndCriteria | endCriteria_ |
| optimization end criteria | |
| Integer | functionEvaluation_ |
| number of evaluation of cost function and its gradient | |
| Integer | gradientEvaluation_ |
| Real | functionValue_ |
| function and gradient norm values of the last step | |
| Real | squaredNorm_ |
| Array | x_ |
| current values of the local minimum and the search direction | |
| Array | searchDirection_ |
